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计算机系统应用英文版:2022,31(12):359-367
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基于演化博弈的网络信息体系资源优选
(1.陆军工程大学 指挥控制工程学院, 南京 210007;2.信息系统需求重点实验室, 南京 210007;3.中国电子科技集团公司第五十四研究所, 石家庄 050081)
Resource Optimization of Network Information-centric System of Systems Based on Evolutionary Game
(1.Command & Control Engineering College, Army Engineering University of PLA, Nanjing 210007, China;2.Key Lab of Information System Requirement, Nanjing 210007, China;3.The 54th Research Institute of China Electronics Technology Group Corporation, Shijiazhuang 050081, China)
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Received:March 27, 2022    Revised:April 22, 2022
中文摘要: 网络信息体系是我军构建的新一代指挥控制作战体系, 具有动态应对任务和环境变化的优势, 通过对全网作战资源实施优选, 实现作战效能最大化. 随着人工智能等技术的发展, 当前主要依靠预案实施的优选方法无法适应智能、无人设备自进化, 且对战场态势覆盖不足. 针对上述缺陷, 本文以防空反导作战体系为例, 研究在物理节点损毁的情况下的资源集成方案求解问题, 采用down-selection模式将资源集成方案求解问题转化为组合优化问题, 通过增加扰动限制改进了演化初始策略形成机制, 提出了基于演化博弈的资源优选方法. 方法在Netlogo平台上进行了仿真, 验证了有效性, 且对比基于遗传算法的资源优选方法, 所求的方案任务完成度平均提高6.4%.
Abstract:The network information-centric system of systems (SoS) is a new generation of command-and-control operational SoS proposed by the PLA, which has the advantage of dynamic response to missions and environmental changes. It optimizes the operational resources of the whole network to maximize operational effectiveness. With the development of artificial intelligence and other technologies, the current optimization method, which mainly depends on the implementation of plans, can neither adapt to the self-evolution of intelligent and unmanned equipment nor cover the battlefield dynamics. Considering the above defects, this study takes the air and missile defense operational SoS as an example to study the solution to the resource integration scheme in the case of physical node damage. The down-selection model is adopted to transform the solution to the resource integration scheme into a combinatorial optimization problem, and the formation mechanism of initial evolutionary strategy is improved by adding disturbance restrictions. Thus, a resource optimization method based on the evolutionary game is proposed. The effectiveness of the method is verified by simulations on the Netlogo platform. Compared with the result of the resource optimization method based on the genetic algorithm, the task completion of the solution by the proposed method is increased by 6.4% on average.
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基金项目:国家自然科学基金青年项目(61802428); 军委科技委基础加强计划技术领域基金(2019-JCJQ-JJ-014)
引用文本:
王楠,张婷婷,左毅,陈镜.基于演化博弈的网络信息体系资源优选.计算机系统应用,2022,31(12):359-367
WANG Nan,ZHANG Ting-Ting,ZUO Yi,CHEN Jing.Resource Optimization of Network Information-centric System of Systems Based on Evolutionary Game.COMPUTER SYSTEMS APPLICATIONS,2022,31(12):359-367